Machine Learning: A Concise Introduction, 2nd Edit ion / Najlacnejšie knihy
Machine Learning: A Concise Introduction, 2nd Edit ion

Kód: 46704747

Machine Learning: A Concise Introduction, 2nd Edit ion

Autor Steven W. (University of Illinois; Carnegie Mellon University) Knox

New edition of a PROSE award finalist title on core concepts for machine learning, updated with the latest developments in the field, now with Python and R source code side-by-side Machine Learning is a comprehensive text on the c ... celý popis

99.13

Bežne: 103.23 €

Ušetríte 4.10 €


Skladom u dodávateľa v malom množstve
Odosielame za 11 - 15 dní

Potrebujete viac kusov?Ak máte záujem o viac kusov, preverte, prosím, najprv dostupnosť titulu na našej zákazníckej podpore.


Pridať medzi želanie

Mohlo by sa vám tiež páčiť

Darčekový poukaz: Radosť zaručená
  1. Darujte poukaz v ľubovoľnej hodnote, a my sa postaráme o zvyšok.
  2. Poukaz sa vzťahuje na všetky produkty v našej ponuke.
  3. Elektronický poukaz si vytlačíte z e-mailu a môžete ho ihneď darovať.
  4. Platnosť poukazu je 12 mesiacov od dátumu vystavenia.

Objednať darčekový poukazViac informácií

Viac informácií o knihe Machine Learning: A Concise Introduction, 2nd Edit ion

Nákupom získate 240 bodov

Anotácia knihy

New edition of a PROSE award finalist title on core concepts for machine learning, updated with the latest developments in the field, now with Python and R source code side-by-side Machine Learning is a comprehensive text on the core concepts, approaches, and applications of machine learning. It presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. New content for this edition includes chapter expansions which provide further computational and algorithmic insights to improve reader understanding. This edition also revises several chapters to account for developments since the prior edition. In this book, the design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods, enabling readers to solve applied problems more efficiently and effectively. This book also includes methods for optimization, risk estimation, model selection, and dealing with biased data samples and software limitations — essential elements of most applied projects. Written by an expert in the field, this important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methodsPresents side-by-side Python and R source code which shows how to apply and interpret many of the techniques coveredIncludes many thoughtful exercises as an integral part of the text, with an appendix of selected solutionsContains useful information for effectively communicating with clients on both technical and ethical topicsDetails classification techniques including likelihood methods, prototype methods, neural networks, classification trees, and support vector machines A volume in the popular Wiley Series in Probability and Statistics, Machine Learning offers the practical information needed for an understanding of the methods and application of machine learning for advanced undergraduate and beginner graduate students, data science and machine learning practitioners, and other technical professionals in adjacent fields.

Parametre knihy

99.13

Obľúbené z iného súdka



Osobný odber Bratislava a 12742 dalších

Copyright ©2008-26 najlacnejsie-knihy.sk Všetky práva vyhradenéSúkromieCookies


Môj účet: Prihlásiť sa
Všetky knihy sveta na jednom mieste. Navyše za skvelé ceny.

Nákupný košík ( prázdny )

Vyzdvihnutie v Zásielkovni
zadarmo nad 59,99 €.

Nachádzate sa: